Muon capture by 3He nuclei followed by proton and deuteron production

The paper describes an experiment aimed at studying muon capture by ${}^{3}\mathrm{He}$ nuclei in pure ${}^{3}\mathrm{He}$ and $\mathrm{D}_2 + {}^{3}\mathrm{He}$ mixtures at various densities. Energy distributions of protons and deuterons produced via $\mu^-+{}^{3}\mathrm{He}\to p+n+n + \nu_{\mu }$ and $\mu^-+{}^{3} \mathrm{He} \to d+n + \nu_{\mu}$ are measured for the energy intervals $10 - 49$ MeV and $13 - 31$ MeV, respectively. Muon capture rates, $\lambda_\mathrm{cap}^p (\Delta E_p)$ and $\lambda_\mathrm{cap}^d (\Delta E_d)$ are obtained using two different analysis methods. The least--squares methods gives $\lambda_\mathrm{cap}^p = (36.7\pm 1.2) {s}^{- 1}$, $\lambda_\mathrm{cap}^d = (21.3 \pm 1.6) {s}^{- 1}$. The Bayes theorem gives $\lambda_\mathrm{cap}^p = (36.8 \pm 0.8) {s}^{- 1}$, $\lambda_\mathrm{cap}^d = (21.9 \pm 0.6) {s}^{- 1}$. The experimental differential capture rates, $d\lambda_\mathrm{cap}^p (E_p) / dE_p$ and $d\lambda_\mathrm{cap}^d (E_d) / dE_d$, are compared with theoretical calculations performed using the plane--wave impulse approximation (PWIA) with the realistic NN interaction Bonn B potential. Extrapolation to the full energy range yields total proton and deuteron capture rates in good agreement with former results.Comment: 17 pages, 13 figures, accepted for publication in PR

Complex speech-language therapy interventions for stroke-related aphasia: the RELEASE study incorporating a systematic review and individual participant data network meta-analysis

Background: People with language problems following stroke (aphasia) benefit from speech and language therapy. Optimising speech and language therapy for aphasia recovery is a research priority. Objectives: The objectives were to explore patterns and predictors of language and communication recovery, optimum speech and language therapy intervention provision, and whether or not effectiveness varies by participant subgroup or language domain. Design: This research comprised a systematic review, a meta-analysis and a network meta-analysis of individual participant data. Setting: Participant data were collected in research and clinical settings. Interventions: The intervention under investigation was speech and language therapy for aphasia after stroke. Main outcome measures: The main outcome measures were absolute changes in language scores from baseline on overall language ability, auditory comprehension, spoken language, reading comprehension, writing and functional communication. Data sources and participants: Electronic databases were systematically searched, including MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Linguistic and Language Behavior Abstracts and SpeechBITE (searched from inception to 2015). The results were screened for eligibility, and published and unpublished data sets (randomised controlled trials, non-randomised controlled trials, cohort studies, case series, registries) with at least 10 individual participant data reporting aphasia duration and severity were identified. Existing collaborators and primary researchers named in identified records were invited to contribute electronic data sets. Individual participant data in the public domain were extracted. Review methods: Data on demographics, speech and language therapy interventions, outcomes and quality criteria were independently extracted by two reviewers, or available as individual participant data data sets. Meta-analysis and network meta-analysis were used to generate hypotheses. Results: We retrieved 5928 individual participant data from 174 data sets across 28 countries, comprising 75 electronic (3940 individual participant data), 47 randomised controlled trial (1778 individual participant data) and 91 speech and language therapy intervention (2746 individual participant data) data sets. The median participant age was 63 years (interquartile range 53–72 years). We identified 53 unavailable, but potentially eligible, randomised controlled trials (46 of these appeared to include speech and language therapy). Relevant individual participant data were filtered into each analysis. Statistically significant predictors of recovery included age (functional communication, individual participant data: 532, n = 14 randomised controlled trials) and sex (overall language ability, individual participant data: 482, n = 11 randomised controlled trials; functional communication, individual participant data: 532, n = 14 randomised controlled trials). Older age and being a longer time since aphasia onset predicted poorer recovery. A negative relationship between baseline severity score and change from baseline (p < 0.0001) may reflect the reduced improvement possible from high baseline scores. The frequency, duration, intensity and dosage of speech and language therapy were variously associated with auditory comprehension, naming and functional communication recovery. There were insufficient data to examine spontaneous recovery. The greatest overall gains in language ability [14.95 points (95% confidence interval 8.7 to 21.2 points) on the Western Aphasia Battery-Aphasia Quotient] and functional communication [0.78 points (95% confidence interval 0.48 to 1.1 points) on the Aachen Aphasia Test-Spontaneous Communication] were associated with receiving speech and language therapy 4 to 5 days weekly; for auditory comprehension [5.86 points (95% confidence interval 1.6 to 10.0 points) on the Aachen Aphasia Test-Token Test], the greatest gains were associated with receiving speech and language therapy 3 to 4 days weekly. The greatest overall gains in language ability [15.9 points (95% confidence interval 8.0 to 23.6 points) on the Western Aphasia Battery-Aphasia Quotient] and functional communication [0.77 points (95% confidence interval 0.36 to 1.2 points) on the Aachen Aphasia Test-Spontaneous Communication] were associated with speech and language therapy participation from 2 to 4 (and more than 9) hours weekly, whereas the highest auditory comprehension gains [7.3 points (95% confidence interval 4.1 to 10.5 points) on the Aachen Aphasia Test-Token Test] were associated with speech and language therapy participation in excess of 9 hours weekly (with similar gains notes for 4 hours weekly). While clinically similar gains were made alongside different speech and language therapy intensities, the greatest overall gains in language ability [18.37 points (95% confidence interval 10.58 to 26.16 points) on the Western Aphasia Battery-Aphasia Quotient] and auditory comprehension [5.23 points (95% confidence interval 1.51 to 8.95 points) on the Aachen Aphasia Test-Token Test] were associated with 20–50 hours of speech and language therapy. Network meta-analyses on naming and the duration of speech and language therapy interventions across language outcomes were unstable. Relative variance was acceptable (< 30%). Subgroups may benefit from specific interventions. Limitations: Data sets were graded as being at a low risk of bias but were predominantly based on highly selected research participants, assessments and interventions, thereby limiting generalisability. Conclusions: Frequency, intensity and dosage were associated with language gains from baseline, but varied by domain and subgroup. Future work: These exploratory findings require confirmatory study designs to test the hypotheses generated and to develop more tailored speech and language therapy interventions. Study registration: This study is registered as PROSPERO CRD42018110947. Funding: This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme and will be published in full in Health and Social Care Delivery Research; Vol. 10, No. 28. See the NIHR Journals Library website for further project information. Funding was also provided by The Tavistock Trust for Aphasia

Neuroimaging-based classification of PTSD using data-driven computational approaches: a multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.Stress-related psychiatric disorders across the life spa

Identifying the Big Questions in paleontology: a community-driven project

Paleontology provides insights into the history of the planet, from the origins of life billions of years ago to the biotic changes of the Recent. The scope of paleontological research is as vast as it is varied, and the field is constantly evolving. In an effort to identify “Big Questions” in paleontology, experts from around the world came together to build a list of priority questions the field can address in the years ahead. The 89 questions presented herein (grouped within 11 themes) represent contributions from nearly 200 international scientists. These questions touch on common themes including biodiversity drivers and patterns, integrating data types across spatiotemporal scales, applying paleontological data to contemporary biodiversity and climate issues, and effectively utilizing innovative methods and technology for new paleontological insights. In addition to these theoretical questions, discussions touch upon structural concerns within the field, advocating for an increased valuation of specimen-based research, protection of natural heritage sites, and the importance of collections infrastructure, along with a stronger emphasis on human diversity, equity, and inclusion. These questions offer a starting point—an initial nucleus of consensus that paleontologists can expand on—for engaging in discussions, securing funding, advocating for museums, and fostering continued growth in shared research directions. La paleontología permite conocer la historia del planeta, desde los orígenes de la vida hace miles de millones de años hasta los cambios bióticos de épocas recientes. El ámbito de la investigación paleontológica es tan vasto como variado y está en constante evolución. En un esfuerzo por identificar las “grandes preguntas” de la paleontología, expertos de todo el mundo se reunieron para elaborar una lista de cuestiones prioritarias que el campo puede abordar en los próximos años. Las 89 preguntas aquí presentadas (agrupadas en 11 temas) representan las contribuciones de casi 200 científicos internacionales. Estas preguntas se refieren a temas comunes, entre los que se incluyen los motores y patrones de la biodiversidad, la integración de diferentes tipos de datos a lo largo de escalas espacio-temporales, la aplicación de datos paleontológicos para resolver cuestiones contemporáneas de biodiversidad y clima, y la utilización eficaz de métodos y tecnologías innovadoras para obtener nuevos conocimientos paleontológicos. Además de estos interrogantes teóricos, los debates abordan inquietudes estructurales dentro del campo, y abogan por una mayor valoración de la investigación basada en especímenes, la protección de los sitios del patrimonio natural y la importancia de la infraestructura de las colecciones; junto con un mayor énfasis en la diversidad humana, la equidad y la inclusión. Estas preguntas representan un punto de partida—un núcleo inicial de consenso que los paleontólogos pueden ampliar—para fomentar debates, obtener financiación, abogar por el apoyo a los museos y estimular el crecimiento continuo en direcciones de investigación compartidas. La paleontologia offre spunti fondamentali per comprendere la storia del pianeta, dalle origini della vita miliardi di anni fa fino ai cambiamenti biotici più recenti. L’ambito della ricerca paleontologica è tanto vasto quanto diversificato e rappresenta un campo in continua evoluzione. In questo studio, esperti provenienti da tutto il mondo si sono riuniti per redigere un elenco di “Grandi Domande” prioritarie che la paleontologia potrà affrontare nei prossimi anni. Le 89 domande qui presentate, raggruppate in 11 temi, rappresentano il contributo di circa 200 scienziati internazionali. Queste domande riguardano tematiche come i meccanismi e i pattern di biodiversità, l’integrazione di varie tipologie di dati su scale spazio-temporali multiple, l’applicazione delle conoscenze paleontologiche ai problemi attuali della crisi climatica e della biodiversità, e l’uso efficace di metodi e tecnologie innovative per ottenere nuove intuizioni paleontologiche. Oltre a questi temi teorici, la discussione si focalizza su problematiche strutturali del campo, promuovendo una maggiore valorizzazione della ricerca basata sugli esemplari, la protezione dei siti di interesse culturale e paleontologico, e l’importanza delle infrastrutture per preservare le collezioni, insieme a una crescente enfasi su un apporto multiculturale, equo e inclusivo. Queste domande costituiscono un punto di partenza—un nucleo di consenso iniziale che i paleontologi possono espandere—per avviare discussioni, ottenere finanziamenti, promuovere i musei e favorire una crescita continua verso direzioni condivise di ricerca